GenAI Data Scientist

Responsibilities:
We are looking for GenerativeAI Data Scientist to develop solutions that ensure federal clients can implement safe, secure, equitable, and privacy-enhancing AI/ML. The Senior Data Scientist will work at the forefront of responsible AI, helping move the sector beyond frameworks to tangible practices. We are looking for more than just a "Senior Data Scientist", but a technologist and thought leader with excellent communication and customer service skills and a passion for data and problem solving.

Key Responsibilities:

• Rigorously evaluate AI/ML development tools and techniques, technical architecture, and data sets to identify AI related risks and policy implications.
• Develop innovative solutions to operationalize AI policy requirements by embedding them in data and model pipelines.
• Develop, test, and support strategies to test and measure AI/ML bias, accuracy, and fairness.
• Develop and implement solutions to anonymize / sanitize both structured and unstructured data sets.
• Translate AI governance standards into technical SOPs. Develop clear documentation and guidance.
• Serve as a trusted advisor and technical resource to teams developing, deploying, and procuring AI to build federal partners' capacity to use AI responsibly and effectively.
• Support policy experts to develop relevant, practical AI policies and governance standards.
• Support the operationalization of the NIST AI Risk Management Framework.
• Develop Steampunk's thought leadership on Responsible AI best practices; represent Steampunk in industry forums.
• You will contribute to the growth of our Data Exploitation and AI Practice!

Qualifications:

• Ability to hold a position of public trust with the US government.
• Master's degree and 3 years of relavent experience; OR
  • Bachelor's degree and 5 years of relavent experience; OR
  • No degree and 9 years of relavent experience
• Possesses at least one professional certification relevant to the technical service provided. Maintain a certification relevant to the product being deployed and/or maintained.
• 5-7 years industry experience developing AI/ML solutions and a passion for using data science to solve complex problems.
• 5-7 years industry experience in SQL, Python, R, Scala, Java, or similar language
• 5-7 years industry experience in Cloud data analytics (AWS, Azure, or GCP) with tools such as AWS SageMaker, Azure Synapse, etc.
• Deep commitment to responsible, ethical AI and a comprehensive awareness of AI's social, civil, privacy, and legal implications. Awareness of and experience applying AI risk management frameworks a plus.
• Experience translating technical concepts to a variety of technical and non-technical audiences.
• Expertise in conducting data science in sensitive contexts and applying best technical practices in data privacy, anonymization, and data protection.
• Expertise applying best practices to maintain data integrity (working with both structured and unstructured data).
• Demonstrated experience with TensorFlow, Keras, Torch, or other Deep Learning tools and frameworks.
• Experience conducting bias testing and implementing strategies to mitigate bias; experience measuring AI fairness a plus.
• Experience working with LLMs and generative AI models; experience automating the anonymization of unstructured data a plus.
• Experience with semantic search engines such as AWS Kendra, Azure Cognitive Search, or similar tool is a plus.
• Data visualization experience in Tableau, Power BI, D3, ArcGIS, or similar is a plus.